Transactions on Emerging Telecommunications Technologies最新文献

{"title":"Deep Learning With Harmonic Elk Herd Optimization for Spectrum Sensing With Cyclostationary in Cognitive Radio Network","authors":"Abdul Hameed Ansari,&nbsp;Sanjay M. Gulhane","doi":"10.1002/ett.70215","DOIUrl":"https://doi.org/10.1002/ett.70215","url":null,"abstract":"<div>\u0000 \u0000 <p>In Cognitive Radio (CR), effective spectrum utilization is regarded as vital to enhance the spectrum efficacy and to accommodate the need for wireless communication services. Spectrum sensing is more essential in CR networks for permitting spectrum prospects without any harmfulness to Primary Users (PUs). However, existing spectrum sensing approaches depend on energy detection, which leads to various disadvantages, like noise sensitivity, ambiguity in detecting weak signals, and fluctuation in background noises. Hence, this paper introduces a new technique termed Harmonic Elk Herd Optimization (HEHO)-PyramidNet+ Kernel Least Mean Square (HEHO-PyramidNet+KLMS) for spectrum sensing in CR networks. First, the signal is collected from the simulated CR system network. Next, the cyclic spectrum is extracted, then the spectrum sensing is carried out by Kernel Least Mean Square (KLMS) filter. On the other hand, the extracted cyclic spectrum is subjected to spectrum sensing, which is performed using PyramidNet. Here, the PyramidNet is tuned using Harmonic Elk Herd Optimizer (HEHO). Afterwards, the attained spectrum sensing outcomes are integrated using the Average Fusion approach. The HEHO-PyramidNet + KLMS measured a maximum probability of detection, throughput, and energy efficiency of 0.919, 91.77 Mbps, and 94.88 bits/J, and a minimum probability of false alarm of 0.089 and a detection time of 21.54 ms.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 8","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144666377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ASCON-MNASNET: An Effective Data Privacy and Security Framework in Cloud Environment","authors":"Jayaprakash Jayachandran,&nbsp;Dahlia Sam,&nbsp;N. Kanya","doi":"10.1002/ett.70218","DOIUrl":"https://doi.org/10.1002/ett.70218","url":null,"abstract":"<div>\u0000 \u0000 <p>As cloud computing continues to proliferate, users are becoming more concerned about the security and privacy of their data, particularly in light of the growing incidences and complexity of cyberattacks. Therefore, it has become imperative for both individuals and organizations to implement a privacy-preserving intrusion detection system (IDS) to secure the data and detect intrusions. Previously available methods are often inadequate, as they may not effectively balance the need for robust security with the preservation of user privacy, leading to potential vulnerabilities and a lack of trust among clients. To overcome these obstacles, this article introduces CryptoIDS, a novel privacy-preserving IDS that closely combines deep learning-based attack detection with lightweight cryptography. To protect cloud data privacy, CryptoIDS specifically uses a lightweight encryption technique based on ASCON and a CondenseNet-MNasNet hybrid deep learning model for precise and rapid intrusion detection. The framework was thoroughly tested on three benchmark datasets: Cleveland (for privacy evaluation), BoT-IoT and IoT-23 (for security evaluation). Experimental results show that CryptoIDS obtained high detection accuracies of 99.67% on the BoT-IoT dataset and 99.45% on the IoT-23 dataset and improved encryption performance by over 13.89% when compared to current cryptographic algorithms. These findings establish CryptoIDS as a highly effective solution for enhancing both data security and privacy protection in cloud environments.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 8","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144666384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-Objective Resource Optimization in UAV-Enabled Heterogeneous Cellular Networks Using Serverless Federated Learning and Power-Domain NOMA","authors":"Qinghua Song,&nbsp;Junru Yang,&nbsp;Amin Mohajer","doi":"10.1002/ett.70210","DOIUrl":"https://doi.org/10.1002/ett.70210","url":null,"abstract":"<div>\u0000 \u0000 <p>The integration of unmanned aerial vehicles (UAVs) into cellular networks has emerged as a promising solution to enhance connectivity and service quality in both urban and remote areas. In this paper, we propose a comprehensive framework that combines multi-agent deep learning with backhaul traffic optimization to effectively manage resources in UAV-enabled communication networks. By leveraging the capabilities of intelligent reflecting surfaces (IRS) and cell-free communication strategies, our approach aims to optimize backhaul traffic, ensuring seamless data transmission and improved network throughput. Our methodology involves a dynamic resource allocation mechanism that utilizes multi-agent deep learning to accurately predict network demands and adaptively allocate resources. The process begins with the collection of real-time network data, including user demand, traffic patterns, and UAV positions. This data is then fed into a deep learning model, where multiple agents collaboratively analyze and predict future network requirements. Based on the predictions, the resource allocation mechanism dynamically adjusts the distribution of resources, such as bandwidth and power, to meet the anticipated demand. This adaptive strategy enables the network to efficiently handle varying traffic loads, reducing congestion and latency. Furthermore, our backhaul traffic optimization technique focuses on minimizing the energy consumption of UAVs while maximizing their coverage and connectivity. By optimizing the flight paths and altitudes of UAVs, we ensure that they provide optimal coverage with minimal energy expenditure. Additionally, the IRS-assisted communication further enhances signal quality, reducing the need for high-power transmissions and thus conserving energy. Our simulations show that our framework improves network throughput, energy efficiency, and reliability. It offers a promising way to manage resources in future UAV-enabled communication networks.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 8","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144666385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Comprehensive Study on Leveraging Serverless Dew Computing for Advanced Data Privacy","authors":"SanatKumar Sahoo,&nbsp;Supriya Panigrahy,&nbsp;Madhav Shantkumar Bhat,&nbsp;Rojalina Priyadarshini","doi":"10.1002/ett.70193","DOIUrl":"https://doi.org/10.1002/ett.70193","url":null,"abstract":"<div>\u0000 \u0000 <p>Serverless dew computing, an innovative merger of serverless and dew computing, deploys serverless functions at the edge of networks near users and data devices, contrasting centralized clouds. Dew computing combines cloud principles with end-user devices like PCs and phones, enhancing experiences beyond traditional clouds and addressing connectivity dependence. It stands out for independence and collaboration. Despite its youth, dew computing reshapes cloud resource utilization, blending cloud capabilities with local devices for reliability, efficiency and user-friendliness. Serverless edge computing combines both paradigms by deploying serverless functions onto edge devices for swift data processing, easing cloud provider burdens. This research delves into serverless dew computing, focusing on parameter analysis. It examines the adoption, challenges and prospects of this edge paradigm, spotlighting potential disruptions. The data selection process is carried out using the guidelines provided by the Prisma tool. The study scrutinizes around 50 papers, analyzing methodologies, challenges, results and parameters. It spans serverless dew computing's foundational concepts, industry applications, advantages over clouds and its role in data privacy.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 7","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144647672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Efficient Multiuser Threshold–Based Dynamic Cipher Puzzle With Secure Key Generation for DoS Attacks in Smart Grid Applications","authors":"N. Sumalatha,&nbsp;K. Baskaran","doi":"10.1002/ett.70204","DOIUrl":"https://doi.org/10.1002/ett.70204","url":null,"abstract":"<div>\u0000 \u0000 <p>Denial-of-service (DoS) attacks in smart grid applications involve malicious attempts to disrupt or compromise the availability and functionality of the grid's services. These attacks aim to overwhelm the smart grid's assets, including communication infrastructures or sensor nodes, rendering them inaccessible or inoperable. Smart grid applications face challenges from DoS attacks, causing communication disruption, latency, and data transfer issues. Wireless sensor nodes are vulnerable to resource depletion, impacting data collection. Ensuring resilience involves dynamic authentication and efficient cryptographic protocols. To effectively address challenges in smart grid applications, the innovative Multiuser Threshold–based Dynamic Cipher Puzzle (MT-DCP) is introduced. Using a threshold function, MT-DCP minimizes sender-side delays and dynamically tailors puzzle strength for each solution. This system integrates the Improved Secure Key Generation utilizing Enhanced Identity-Based Encryption (ISKG-EIBE), enhancing overall security. Noteworthy results include an efficient 0.0091 ms computational overhead and an impressive 99.32% key sensitivity, illustrating its robustness in countering DoS attacks. Real-time implementation of the proposed work is achieved by utilizing Python3 on the Raspberry Pi 3B+ model, resulting in 6.5 KB memory usage, 168.58 ms execution time, and 3.58 J energy consumption. The holistic methodology employed by MT-DCP establishes it as a highly efficient resolution for countering false data injection concerns and ensuring the robustness of smart grid applications.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 7","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144589627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Index Code Design for Index Coded-NOMA Transmission in VANETs","authors":"P. Sreelakshmi,&nbsp;Jesy Pachat,&nbsp;P. P. Deepthi,&nbsp;Nujoom Sageer Karat,&nbsp;B. Sundar Rajan","doi":"10.1002/ett.70209","DOIUrl":"https://doi.org/10.1002/ett.70209","url":null,"abstract":"<div>\u0000 \u0000 <p>Data distribution in vehicular ad hoc networks (VANETs) is delay sensitive in nature. Therefore, the development of efficient schemes to serve the demands of users with fewer transmissions is beneficial. Index coded NOMA (IC-NOMA) can provide improved spectral and power efficiency in VANETs. The improved performance of IC-NOMA can be achieved only if the index code design is suitably developed to fit with NOMA transmission principles. In this study, we consider a practical data dissemination scenario for VANETs where vehicles traveling at different speeds demand common data, such as popular multimedia content. For such a data distribution problem, a lower bound on the number of IC-NOMA transmissions is derived. This work also presents an index code solution for IC-NOMA transmission. The IC-NOMA with index code solution proposed in this work demonstrates enhanced performance in terms of power consumption, bandwidth utilization, and computational complexity.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 7","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to “Exploring Illumination and Communication: A Comprehensive Analysis of LED Lighting in Modern Interior Architectural Designs, Enhanced by Weighted Sum Model and Cluster Analysis for Informed Lighting Selection”","authors":"","doi":"10.1002/ett.70212","DOIUrl":"https://doi.org/10.1002/ett.70212","url":null,"abstract":"<p>K. Sathiamoorthy and I. Ganesan, “Exploring Illumination and Communication: A Comprehensive Analysis of LED Lighting in Modern Interior Architectural Designs, Enhanced by Weighted Sum Model and Cluster Analysis for Informed Lighting Selection,” <i>Transactions on Emerging Telecommunications Technologies</i> 36 (2025): e70036, https://doi.org/10.1002/ett.70036.</p><p>The statements in the Acknowledgement section were mistakenly repeated. The correct statements should read:</p><p>The authors express their heartfelt gratitude to Mepco Schlenk Engineering College (Autonomous), Sivakasi for providing the opportunity and resources to successfully complete this research. The authors also extend their sincere thanks to the editors and anonymous reviewers for their invaluable comments and suggestions which significantly improved the quality and precision of this article.</p><p>The online version of the article has also been updated.</p><p>We apologize for this error.</p>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 7","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ett.70212","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144519717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy-Efficient Computation Offloading Scheme for Vehicular Edge Computing Using Improved Golden Eagle Optimization Algorithm","authors":"S. Syed Abuthahir,&nbsp;J. Selvin Paul Peter","doi":"10.1002/ett.70191","DOIUrl":"https://doi.org/10.1002/ett.70191","url":null,"abstract":"<div>\u0000 \u0000 <p>The increasing processing demands of vehicle applications pose a major challenge for the Internet of Vehicles (IoVs). Multi-access edge computing (MEC) offloads computation-intensive activities to edge servers, significantly enhancing computing capacity and extending vehicle battery life. Nevertheless, traditional offloading strategies fail to effectively balance computation tasks among vehicles and edge servers, resulting in suboptimal resource utilization and increased energy consumption. Therefore, an Energy-Efficient Computation Offloading Scheme for Vehicular Edge Computing utilizing Improved Golden Eagle Optimization Algorithm (EECO-VEC-IGEOA) is proposed. An Improved Golden Eagle Optimization Algorithm (IGEOA) is designed to optimize energy-efficient computation offloading in vehicular edge computing networks (VECN). By dynamically allocating computation tasks between vehicles and edge servers depending on real-time conditions, the EECO-VEC-IGEOA model aims to improve overall network performance and energy efficiency. The EECO-VEC-IGEOA method reduces energy consumption by 14.62%, 16.84%, and 19.16%, and task completion time by 15.84%, 18.92%, and 20.69% compared to the existing approaches.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 7","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144519718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distributed Timber Trading Mechanism Based on Blockchain Smart Contracts","authors":"Robertas Damaševičius,&nbsp;Rytis Maskeliūnas","doi":"10.1002/ett.70194","DOIUrl":"https://doi.org/10.1002/ett.70194","url":null,"abstract":"<div>\u0000 \u0000 <p>The timber industry, characterized by its vast supply chains and complex trade networks, faces challenges such as inefficiency, vulnerability to fraud, lack of transparency, and fairness in trading practices. Addressing these challenges, we propose a distributed timber trading mechanism based on blockchain technology and smart contracts. The mechanism introduces a strategy to match timber trading orders and a model to manage trader credibility. Our study also developed a credit management model that uses the entropy weight method to assess the credibility of traders based on their transaction history and their commitment to sustainable practices. The key findings and results of this study underscore the potential of blockchain technology and smart contracts to revolutionize the timber industry by addressing its long-standing challenges. The distributed timber trading mechanism that we propose sets the foundation for a more sustainable, transparent, and efficient marketplace.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 7","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144514909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improved dDQL: A Double Deep Q-Learning Enabled Localization for Internet of Underwater Things","authors":"Nellore Kapileswar,&nbsp;Judy Simon,&nbsp;Polasi Phani Kumar,&nbsp;Thomas M Chen,&nbsp;Sathiyanarayanan Mithileysh","doi":"10.1002/ett.70207","DOIUrl":"https://doi.org/10.1002/ett.70207","url":null,"abstract":"<div>\u0000 \u0000 <p>Reliable sensor node localization is essential for internet of underwater things (IoUT) applications because it allows management, communication, and sensing in large, uncharted oceanic environments. This research focuses on developing a learning-enabled node localization model for IoUT using autonomous underwater vehicles (AUVs). To estimate the locations of AUVs, active and passive sensor nodes, a double deep Q-learning (dDQL) based localization algorithm is introduced. AUVs serve as mobile anchor nodes, and the algorithm uses an online value iteration process to optimize node locations. Active sensor nodes initiate the localization process by transmitting messages, whereas passive sensor nodes determine their location without sending signals. Furthermore, the proposed algorithm for exaggerated crayfish optimization (ExCo) utilizes the selection of optimal actions. The proposed dDQL with ExCo acquired RMSE, localization error, time, delay, throughput, and energy consumption of 1.44E-07 m, 7.19E-08 m, 16153.16 s, 13.08 s, 0.98 bps, and 0.35 J, respectively.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 7","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144482031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}